A robust deep learning approach for photovoltaic power forecasting based on feature selection and variational mode decomposition

Accurate forecasting of photovoltaic (PV) power is essential for effective grid integration and energy management, particularly in solar-rich regions such as Algeria. This study presents a robust forecasting framework that combines advanced feature selection techniques with deep learning architectu...

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Autors principals:	Mokhtar Ali, Abdelkerim Souahlia, Abdelhalim Rabehi, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem
Format:	Artigo
Idioma:	Inglês
Publicat:	Nigerian Society of Physical Sciences 2025-08-01
Col·lecció:	Journal of Nigerian Society of Physical Sciences
Matèries:	PV power Renewable energy Feature selection Artificial Neural Networks Forecasting
Accés en línia:	https://journal.nsps.org.ng/index.php/jnsps/article/view/2795
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